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Refer to the Exhibit Practice Questions

Practise CompTIA Data+ (DA0-002) practice questions — original exam-style scenarios covering every exam domain, with detailed explanations, wrong-answer analysis, and common exam traps.

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DA0-002
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CompTIA
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Scenario guide

How to approach refer to the exhibit practice questions

Practise exhibit-style questions that ask you to read a topology, table, command output or diagram before choosing the best answer.

Quick answer

Exhibit-style questions test whether you can read a topology, command output, diagram or table before choosing the best answer.

How to extract the relevant detail from an exhibit.

How topology, command output or routing information affects the answer.

How to avoid answering from memory before reading the evidence.

How to map the exhibit back to the exam objective.

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Practice set

Practice scenarios

Question 1hardmultiple choice
Full question →

Refer to the exhibit. A data architect is designing a data dictionary for a relational database. Based on the exhibit, which data concept is being illustrated?

Exhibit

{
  "employee": {
    "emp_id": { "type": "integer", "nullable": false, "primary_key": true },
    "name": { "type": "string", "nullable": false },
    "email": { "type": "string", "nullable": true, "unique": true },
    "department": { "type": "string", "nullable": true }
  }
}
Question 2mediummultiple choice
Full question →

Refer to the exhibit. A data analyst is trying to extract data from a SQL Server database but receives the error. Which configuration change should the analyst recommend to the database administrator?

Exhibit

Error: 2024-03-15 10:32:45 ERROR [DataExtractor] Failed to connect to source database 'SalesDB' on server 10.0.0.50:1433. Error: Login failed for user 'dataminer'. Reason: An attempt to login using SQL authentication failed. Server is configured for Windows authentication only.
Question 3hardmultiple choice
Full question →

Based on the exhibit, what is the most likely cause of the import failure?

Exhibit

Refer to the exhibit.

Data Import Log:
[2024-03-15 10:22:34] INFO: Starting import from source 'sales_raw.csv'
[2024-03-15 10:22:35] WARN: Row 1502: 'price' field contains non-numeric value '12.5A'. Skipping row.
[2024-03-15 10:22:36] ERROR: Row 3450: 'date' field value '2024-02-30' is invalid. Import halted.
[2024-03-15 10:22:36] INFO: Import process terminated with errors.
Question 4easymultiple choice
Full question →

Refer to the exhibit. What data quality issue is indicated?

Exhibit

2023-08-15 14:32:10 ERROR: Data conversion failed for column 'salary' in row 45: value 'N/A' cannot be converted to numeric.
Question 5mediummultiple choice
Full question →

Refer to the exhibit. Which type of data is the field "region"?

Exhibit

{
  "report": "Analytics",
  "filters": [
    {"field": "transaction_date", "operator": ">=", "value": "2023-01-01"},
    {"field": "region", "operator": "=", "value": "West"}
  ],
  "metrics": ["revenue", "units_sold"]
}
Question 6hardmultiple choice
Full question →

Refer to the exhibit. A data analyst is creating a report that includes customer transaction data from 6 years ago. According to the policy, what should the analyst do?

Exhibit

Refer to the exhibit.
{
  "policy": {
    "data_retention": {
      "customer_transactions": "5 years",
      "employee_records": "7 years",
      "marketing_leads": "2 years"
    },
    "data_sharing": {
      "third_party_vendors": "anonymized only",
      "internal_departments": "as needed"
    },
    "data_quality": {
      "missing_values": "flag and report",
      "outliers": "review quarterly"
    }
  }
}
Question 7hardmultiple choice
Full question →

A time series of monthly sales data exhibits a clear upward trend over several years, with consistent peaks each December. Which components are present in this series?

Question 8mediummultiple choice
Full question →

The exhibit shows a JSON schema for a dataset. Which statement correctly describes the data types represented?

Exhibit

Refer to the exhibit.

{
  "fields": [
    {"name": "customer_id", "type": "integer"},
    {"name": "age", "type": "integer"},
    {"name": "income", "type": "float"},
    {"name": "education", "type": "string"}
  ]
}
Question 9mediummultiple choice
Full question →

Refer to the exhibit. A data analyst notices that direct S3 access to files outside the "incoming/" prefix is blocked. Which data governance principle does this policy enforce?

Exhibit

{
  "policy": {
    "effect": "Allow",
    "action": ["s3:GetObject"],
    "resource": "arn:aws:s3:::data-bucket/*",
    "condition": {
      "StringEquals": {"s3:prefix": "incoming/"}
    }
  }
}
Question 10hardmultiple choice
Full question →

Refer to the exhibit. Before running the code, the original salary column had 50 missing values. The median was calculated as 52000. After imputation, which of the following statements is true?

Exhibit

Refer to the exhibit.

Python pandas code and output:
```
import pandas as pd
df = pd.read_csv('employees.csv')
df['salary'].fillna(df['salary'].median(), inplace=True)
print(df['salary'].describe())
```
Output:
```
count    1000.000000
mean     55000.000000
std      15000.000000
min      25000.000000
25%      45000.000000
50%      52000.000000
75%      65000.000000
max     120000.000000
Name: salary, dtype: float64
```
Question 11hardmultiple choice
Full question →

Refer to the exhibit. Which data quality dimension is being violated?

Exhibit

2024-01-15 10:23:45 ERROR: DataTypeMismatchException - Column 'age' contains mixed data types: INT and VARCHAR. Pipeline 'user_profile_etl' failed.
Question 12mediummultiple choice
Full question →

Refer to the exhibit. Which data concept does this exhibit best represent?

Exhibit

Refer to the exhibit.
Exhibit:
{
  "type": "object",
  "properties": {
    "customerId": { "type": "integer" },
    "name": { "type": "string" },
    "orders": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "orderId": { "type": "integer" },
          "total": { "type": "number" }
        }
      }
    }
  }
}
Question 13easymultiple choice
Full question →

Refer to the exhibit. An Avro schema is defined as shown. Which data design concept does this represent?

Exhibit

{
  "schema": {
    "type": "struct",
    "fields": [
      { "name": "id", "type": "int", "nullable": false },
      { "name": "name", "type": "string", "nullable": true },
      { "name": "email", "type": "string", "nullable": true }
    ]
  }
}
Question 14easymultiple choice
Full question →

Refer to the exhibit. The data shown is an example of which data concept?

Exhibit

Refer to the exhibit.
Exhibit:
ID,Name,Age,Salary
1,John,32,50000
2,Jane,28,60000
3,Bob,45,55000
Question 15mediummultiple choice
Full question →

Refer to the exhibit. A data analyst attempts to visualize the dataset but receives a permission error. The analyst's username is 'analyst2'. What is the most likely cause?

Exhibit

{
  "dataset": {
    "access": {
      "users": ["admin", "analyst"],
      "permissions": ["read", "write"]
    }
  }
}

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